prithivMLmods/Basically-Human-4B-f32-GGUF
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Model: prithivMLmods/Basically-Human-4B-f32-GGUF
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2026-09-01 02:02:13 +08:00
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---
license: apache-2.0
language:
- en
base_model:
- GreenerPastures/Basically-Human-4B
library_name: transformers
pipeline_tag: text-generation
tags:
- text-generation-inference
---
# **Basically-Human-4B-f32-GGUF**
> Basically-Human-4B is a 4 billion parameter language model based on the Qwen3 4B architecture, fine-tuned specifically for immersive and emotionally resonant roleplaying and character interaction. It excels in maintaining in-character consistency, crafting believable dialogue, and driving dynamic storytelling, making it ideal for text-based roleplay, NPC simulation, and interactive fiction applications. The model uses the ChatML instruction format to structure multi-turn conversations with clear role delineation. Basically-Human-4B was fine-tuned on a diverse set of instruction and roleplaying datasets, including various curated and cleaned instruction data from multiple sources. It offers GGUF quantized versions for ease of deployment while delivering compact yet capable performance in roleplay scenarios.
## Model Files
| File Name | Quant Type | File Size |
| - | - | - |
| Basically-Human-4B.BF16.gguf | BF16 | 8.05 GB |
| Basically-Human-4B.F16.gguf | F16 | 8.05 GB |
| Basically-Human-4B.F32.gguf | F32 | 16.1 GB |
| Basically-Human-4B.Q2_K.gguf | Q2_K | 1.67 GB |
| Basically-Human-4B.Q3_K_L.gguf | Q3_K_L | 2.24 GB |
| Basically-Human-4B.Q3_K_M.gguf | Q3_K_M | 2.08 GB |
| Basically-Human-4B.Q3_K_S.gguf | Q3_K_S | 1.89 GB |
| Basically-Human-4B.Q4_K_M.gguf | Q4_K_M | 2.5 GB |
| Basically-Human-4B.Q4_K_S.gguf | Q4_K_S | 2.38 GB |
| Basically-Human-4B.Q5_K_M.gguf | Q5_K_M | 2.89 GB |
| Basically-Human-4B.Q5_K_S.gguf | Q5_K_S | 2.82 GB |
| Basically-Human-4B.Q6_K.gguf | Q6_K | 3.31 GB |
| Basically-Human-4B.Q8_0.gguf | Q8_0 | 4.28 GB |
## Quants Usage
(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):
![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)

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{
"model_type": "qwen3"
}

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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}